Error-correcting output code (ECOC)[1,2] 


A length-\(n\) binary or ternary (over \(\{\pm 1,0\}\)) block code used to convey information about classes to classifiers in multiclass machine learning. Rows of the code's generator matrix denote different classes, while columns correspond to classifiers.

A data-driven ECOC (DECOC) [3] is an ECOC whose design takes into account features of the data that is to be classified. Not always decoded using the Hamming metric.


Standard Hamming-distance decoding [4].Inverse Hamming decoding [5].Euclidean-distance decoding or attenuated Euclidean decoding [6].Loss-based decoding [2].Probabilistic-based decoding [7].


Multiclass problems in machine learning, relevant to facial recognition [8,9], text recognition [10], or digit classification [11].


See [12][13; Ch. 6] for overviews of ECOCs.See [14] for a library of ECOCs.




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Zoo Code ID: ecoc

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“Error-correcting output code (ECOC)”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2024.
@incollection{eczoo_ecoc, title={Error-correcting output code (ECOC)}, booktitle={The Error Correction Zoo}, year={2024}, editor={Albert, Victor V. and Faist, Philippe}, url={} }
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“Error-correcting output code (ECOC)”, The Error Correction Zoo (V. V. Albert & P. Faist, eds.), 2024.